International Scientific Journal of Engineering and Management

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ISSN: 2583-6129

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Impact of AI-Powered Personalized Financial Services on Customer Trust and Digital Banking Adoption in the Banking Sector

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Published 13 July 2026
Updated 22 July 2026

Impact of AI-Powered Personalized Financial Services on Customer Trust and Digital Banking Adoption in the Banking Sector

 

 

VARUN C V
Department of Management Studies
Dayananda Sagar College of Engineering

 

JAYASHREE K
Assistant Professor
Department of Management Studies
Dayananda Sagar College of Engineering

 

 

Abstract

The rapid diffusion of artificial intelligence (AI) across the financial services industry has transformed how banks design, deliver, and personalize customer offerings. This study investigates the impact of AI-powered personalized financial services on customer trust and the adoption of digital banking platforms. Drawing on the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and trust theory, this research develops an integrated conceptual framework linking perceived personalization, perceived usefulness, perceived ease of use, data privacy and security concerns, and algorithmic transparency to customer trust and behavioral intention to adopt digital banking. A quantitative, cross-sectional survey design is employed, and the resulting data are analyzed using descriptive statistics, reliability analysis, correlation analysis, and multiple regression / structural equation modeling. The findings indicate that AI-driven personalization has a statistically significant positive relationship with customer trust, and that customer trust, in turn, mediates the relationship between personalization and digital banking adoption. Perceived data security emerges as a critical boundary condition that strengthens or weakens this relationship. The study contributes to the growing body of literature on AI adoption in financial services by empirically validating the trust-mediated adoption pathway and offers practical recommendations for bank managers, fintech developers, and policymakers seeking to design AI systems that are both effective and trustworthy. Limitations and directions for future research are also discussed.

Keywords: Artificial Intelligence; Personalized Financial Services; Customer Trust; Digital Banking Adoption; Technology Acceptance Model; UTAUT; Financial Technology (FinTech)

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